{"id":"W4240676231","doi":"10.9707/1944-5660.1431","title":"Front Matter","year":2018,"lang":"en","type":"paratext","venue":"The Foundation Review","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Impact","funders":"","keywords":"Front (military); Political science; Geography; Meteorology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001373099,0.0004156853,0.0007598412,0.00006769627,0.0002087151,0.000153615,0.0008733914,0.0001372257,0.8716317],"category_scores_gemma":[0.0000792067,0.0002479468,0.0002605273,0.0002399858,0.0002118978,0.0001391384,0.0001571677,0.0003659944,0.9988387],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002394159,"about_ca_system_score_gemma":0.0001703715,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004417795,"about_ca_topic_score_gemma":0.00001320645,"domain_scores_codex":[0.9974142,0.0006916401,0.0006886754,0.00042566,0.0004778588,0.0003020111],"domain_scores_gemma":[0.9971429,0.00007476966,0.0008708117,0.00156048,0.0002925007,0.00005858493],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000003381066,0.00001184524,9.105742e-7,0.003288057,0.00006576465,1.822878e-7,0.00001753723,2.575991e-7,0.000003820066,0.00001932654,0.9927125,0.003876443],"study_design_scores_gemma":[0.0000671813,0.00001387817,0.00002975559,0.01119913,0.0003765122,0.00001339695,0.000001028471,0.000002461778,0.000004361143,0.00007208436,0.9879243,0.0002958583],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00000232343,0.2535734,0.0001949855,0.002958793,0.002622358,0.001743699,0.0001175449,0.00005161199,0.7387353],"genre_scores_gemma":[0.000003660331,0.1237658,0.0001077432,0.0117528,0.001536408,0.000308708,0.002918831,0.0001816207,0.8594244],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.1298075,"threshold_uncertainty_score":0.9999973,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04459250040447666,"score_gpt":0.3489237234350734,"score_spread":0.3043312230305967,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}